code: def load_embeddings(filename):
      fin = open(filename, "r")
      node_num, size = [int(x) for x in fin.readline().strip().split()]
      vectors = {}
      while 1:
          l = fin.readline()
          if l == "":
              break
          vec = l.strip().split(" ")
          assert len(vec) == size + 1
          vectors[vec[0]] = [float(x) for x in vec[1:]]
      fin.close()
      assert len(vectors) == node_num
      return vectors
  
file_path: OpenNE/src/openne/classify.py
imports: from __future__ import print_function
  import numpy
  from sklearn.multiclass import OneVsRestClassifier
  from sklearn.metrics import f1_score
  from sklearn.preprocessing import MultiLabelBinarizer
  from time import time
label_desc: Use image node_id 1 for calling a global function with example usage: load_embeddings(filename) and returns: vectors